Data Analysis and Visualization with R for beginners
Data Analysis and Visualization with R for beginners, available at $27.99, has an average rating of 3.95, with 28 lectures, based on 13 reviews, and has 1741 subscribers.
You will learn about Install R and RStudio Create new R Projects Create R variables (objects) Install and load R Packages Import data into R Studio Perform data wrangling on your data Pipe several functions into a dataset using the Pipe function Create data visualizations using graphs Read data into a variable This course is ideal for individuals who are Beginners to data analysis and visualization using R It is particularly useful for Beginners to data analysis and visualization using R.
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Summary
Title: Data Analysis and Visualization with R for beginners
Price: $27.99
Average Rating: 3.95
Number of Lectures: 28
Number of Published Lectures: 28
Number of Curriculum Items: 28
Number of Published Curriculum Objects: 28
Original Price: $27.99
Quality Status: approved
Status: Live
What You Will Learn
- Install R and RStudio
- Create new R Projects
- Create R variables (objects)
- Install and load R Packages
- Import data into R Studio
- Perform data wrangling on your data
- Pipe several functions into a dataset using the Pipe function
- Create data visualizations using graphs
- Read data into a variable
Who Should Attend
- Beginners to data analysis and visualization using R
Target Audiences
- Beginners to data analysis and visualization using R
R is a programming language. R is often used for statistical computing and graphical presentation to analyse and visualize data.
R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible.
One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed.
R is available as Free Software under the terms of the Free Software Foundation’s GNU General Public License in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.
R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes
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an effective data handling and storage facility,
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a suite of operators for calculations on arrays, in particular matrices,
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a large, coherent, integrated collection of intermediate tools for data analysis,
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graphical facilities for data analysis and display either on-screen or on hardcopy, and
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a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.
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R can be extended (easily) via packages. There are about eight packages supplied with the R distribution and many more are available through the CRAN family of Internet sites covering a very wide range of modern statistics.
RStudiois an integrated development environment for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser.
Course Curriculum
Chapter 1: Getting Started
Lecture 1: Introduction
Lecture 2: What is R
Lecture 3: Installing R on Windows
Lecture 4: Installing R on Mac
Lecture 5: What is R Studio
Lecture 6: Installing R studio on Windows
Lecture 7: Installing R Studio on Mac
Lecture 8: Exploring R Studio Default Interface
Lecture 9: Creating a new project in R Studio
Lecture 10: What are Packages
Lecture 11: How to install Packages
Lecture 12: Data sets vs Data frames
Lecture 13: Loading Packages
Chapter 2: Data Analysis & Visualization
Lecture 1: Importing data into R Studio
Lecture 2: How to read data in a csv file with R
Lecture 3: Installing Janitor Package
Lecture 4: Selecting a subset of data
Lecture 5: Performing multiple operations using Pipe operator
Lecture 6: Cleaning columns
Lecture 7: Creating new columns from existing columns
Lecture 8: Create a new R Project
Lecture 9: Load data into new project
Lecture 10: What is Data Wrangling
Lecture 11: Data Wrangling steps
Lecture 12: Importance of data wrangling
Lecture 13: Perform Data Wrangling on Data
Lecture 14: Create a scatter plot
Lecture 15: Create a bar graph
Instructors
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Bluelime Learning Solutions
Making Learning Simple
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 2 votes
- 3 stars: 1 votes
- 4 stars: 3 votes
- 5 stars: 6 votes
Frequently Asked Questions
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Can I take my courses with me wherever I go?
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